Can China get out of soy dilemma? A yield gap analysis of soybean in China

Wang, Yucheng; Ling, Xiaoxia; Ma, Chao; Liu, Changyan; Zhang, Wei; Huang, Jikun; Peng, Shaobing; Deng, Nanyan

doi:10.1007/s13593-023-00897-6

Cited by 8 publications

(3 citation statements)

References 70 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results of this study showed that both (0 nitrogen fertilizer + compound microbial fertilizer) T3 and (50% nitrogen fertilizer + compound microbial fertilizer) T2 reduced the soil capacity compared to (chemical fertilizer alone) T1. Zhang Xiting et al [23] stated that the optimum soil capacity interval for soybean growth is between 1.00 and 1.30 g/cm 3 . Therefore, the soil capacity of the single application of compound microbial fertilizer and the alternative treatment of compound microbial fertilizer in this experiment meets the requirements for soybean growth.…”

Section: Effect Of Chemical Fertilizer With Compound Microbial Fertil...mentioning

confidence: 99%

“…In China, with soybean [1], there is a historical record of its cultivation [2] dating from as early as 4700 years ago. Soybean is one of the world's important oil and grain crops, widely grown in the northeast region of China, Inner Mongolia, Shandong, Henan, Hebei, and other regions [3]. An indispensable part of the soybean production process is the application of fertilizer [4], which can play a direct role in the improvement of soybean yield and quality.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Effect of Chemical Fertilizer with Compound Microbial Fertilizer on Soil Physical Properties and Soybean Yield

Fu,

Ma,

Qiang

et al. 2023

Agronomy

View full text Add to dashboard Cite

Compound microbial fertilizer is a new type of environmentally friendly slow-release fertilizer that can effectively improve the physical and chemical properties of the soil, significantly improve the ecological environment, and promote the sustainable development of agriculture. In this study, we conducted a field experiment to evaluate the impact of different applications of chemical fertilizer combined with composite microbial fertilizer on soil physical properties and soybean yields at Heshan Farm, Heilongjiang Province, China, during 2021–2022. Soybean varieties “Jinyuan 55” and “Keshan 1” were treated with three treatments implemented as follows: T1 (conventional fertilization), T2 (50% N fertilizer + compound microbial fertilizer), and T3 (0 N fertilizer + compound microbial fertilizer). Compared to conventional fertilization (T1 treatment), the application of composite microbial fertilizers (T2 and T3) resulted in a decrease in soil bulk density and an increase in porosity. Notably, we observed that moderate application of the composite microbial fertilizer (T3) led to a decrease in the volume fraction of clay particles and an increase in the volume fraction of sand particles. Furthermore, all treatments exhibited high content of agglomerates larger than 5 mm at 0–20 cm. The application of composite microbial fertilizers (T2 and T3) promoted the formation of large soil agglomerates and reduced the presence of micro-agglomerates smaller than 0.25 mm. In 2021–2022, The soybean yield increased by 13.02% in the T2 treatment compared with the T1 treatment and decreased by 9.34% in the T3 treatment. We concluded that the appropriate application of compound microbial fertilizer can help protect black soil, enhance the self-repair capability of black soil, and improve soybean quality in abnormal precipitation years. These results provide an actionable basis for constructing and developing green fertilizer systems for the soybean industry.

show abstract

Section: Effect Of Chemical Fertilizer With Compound Microbial Fertil...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Effect of Chemical Fertilizer with Compound Microbial Fertilizer on Soil Physical Properties and Soybean Yield

Fu,

Ma,

Qiang

et al. 2023

Agronomy

View full text Add to dashboard Cite

show abstract

“…over 30% of the world's total soybean consumption (Liu and Fan, 2021). Despite being the fourth-largest producer of soybeans after Brazil, the United States, and Argentina, China's self-sufficiency rate is low (FAOSTAT, 2023;Wang et al, 2023). Given the rapid growth of demand and the shortcomings of domestic supply, mapping soybean planting areas across China is crucial for sustainable soybean production and management.…”

mentioning

confidence: 99%

ChinaSoyArea10m: a dataset of soybean planting areas with a spatial resolution of 10 m across China from 2017 to 2021

Mei,

Zhang,

Han

et al. 2023

Preprint

View full text Add to dashboard Cite

Abstract. Soybean, an essential food crop, has witnessed a steady rise in demand in recent years. There is a lack of high-resolution annual maps depicting soybean planting areas in China, despite China being the world’s largest consumer and fourth largest producer of soybeans. To address this gap, we developed a novel method called phenological- and pixel-based soybean area mapping (PPS) based on Sentinel-2 remote sensing images from the Google Earth Engine (GEE) platform. We utilized various auxiliary data (e.g., cropland layer, detailed phenology observations) to select the distinct features that differentiate soybeans most effectively from other crops across various regions. These features were then input for an unsupervised classifier (K-means), and the most likely type was determined by a post-classification method based on dynamic time warping (DTW). For the first time, we generated a dataset of soybean planting areas across China, with a high spatial resolution of 10 meters, spanning from 2017 to 2021 (ChinaSoyArea10m). The R2 values between the mapping results and the census data at both county- and prefecture-level were consistently around 0.85 in 2017–2020. Moreover, the overall accuracy of mapping results at the field level in 2017, 2018, and 2019 were 77 %, 84 % and 88 %, respectively. Compared with the existing 10-m crop-type maps in Northeast China (Cropland Data Layer, CDL) based on field samples and supervised classification methods, the mapping accuracy is significantly improved by 31 % (R2 increases from 0.53 to 0.84) according to their consistency with census data, particularly at the county level. ChinaSoyArea10m is spatially consistent well with the two existing datasets (CDL and GLAD maize-soybean map). ChinaSoyArea10m provides important information for sustainable soybean production and management, as well as agricultural system modeling and optimization. ChinaSoyArea10m can be downloaded from an open-data repository (DOI: https://zenodo.org/doi/10.5281/zenodo.10071426, Mei et al., 2023).

show abstract

Drivers of soybean-based rotations synergistically increase crop productivity and reduce GHG emissions

Yang,

Zou,

Huang

et al. 2024

Agriculture, Ecosystems & Environment

View full text Add to dashboard Cite

Can China get out of soy dilemma? A yield gap analysis of soybean in China

Cited by 8 publications

References 70 publications

Effect of Chemical Fertilizer with Compound Microbial Fertilizer on Soil Physical Properties and Soybean Yield

Effect of Chemical Fertilizer with Compound Microbial Fertilizer on Soil Physical Properties and Soybean Yield

ChinaSoyArea10m: a dataset of soybean planting areas with a spatial resolution of 10 m across China from 2017 to 2021

Drivers of soybean-based rotations synergistically increase crop productivity and reduce GHG emissions

Contact Info

Product

Resources

About